992 datasets found

Confluence is a novel non-Intersection over Union (IoU) alternative to Non-Maxima Suppression (NMS) in bounding box post-processing in object detection.

Large dataset for stereo matching, optical flow, and scene flow estimation

The PartImageNet dataset is a large-scale vehicle part segmentation dataset, containing 24,000 images of 158 classes.

Aerial IR videos of photovoltaic plants for automatic extraction and georeferencing of PV modules

The Human Action Recognition dataset is used for human action recognition tasks.

The dataset used in the paper is Places, a large dataset of 400k pairs of images from the Places 205 dataset and corresponding spoken audio captions.

This dataset is used for density-aware NeRF ensembles.

This dataset is used for few-shot novel view synthesis.

This dataset is used for novel view synthesis and scene reconstruction.

The MVG dataset, which contains 1,009 samples, each with five images of the same person wearing the same garment from five different views.

The proposed method for Multi-View Virtual Try-On (MV-VTON) task, which aims at using the frontal and back clothing to reconstruct the dressing results of a person from multiple...

A dataset of 2000 RGB images for lane detection using SegNet architecture.

A real-world dataset captured by mobile phones and containing quite complex trajectories.

A novel end-to-end method that does not require prior camera parameters to deal with image sequences with complex trajectories.

The proposed method, dubbed Dynamic Hyperpixel Flow, learns to compose hypercolumn features on the fly by selecting a small number of relevant layers from a deep convolutional...

The Oxford RobotCar Dataset is a collection of images and videos of a car driving on various roads and conditions.

The dataset used in the paper is MNIST, CIFAR-10, CIFAR-100, Tiny-ImageNet, and VGG-like.

This paper proposes the use of Neural Radiance Fields (NeRF) as a scene representation for visual localization.

The Cambridge Landmarks dataset contains 5 different large outdoor scenes of landmarks in the city of Cambridge.

The dataset used in this paper is a sparse Resnet50 model, which is a variant of the Resnet50 model with 80% sparsity.